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Merge MK 263:264: Some new functions (coming with NES tests)

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This commit is contained in:
Marcel Kronfeld
2009-04-02 09:43:58 +00:00
parent ce386ba34c
commit 3f4d270524
5 changed files with 140 additions and 35 deletions
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49
src/wsi/ra/math/Jama/Matrix.java
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@@ -11,6 +11,7 @@ import java.util.Locale;
import wsi.ra.math.Jama.util.Maths;
import eva2.gui.BeanInspector;
import eva2.tools.Mathematics;
import eva2.tools.Pair;
@@ -232,6 +233,17 @@ public class Matrix implements Cloneable, java.io.Serializable {
return A;
}
/**
* Produce a matrix with the diagonal entries of the instance. All others are set to zero.
*
* @return a diagonal matrix
*/
public Matrix getDiagonalMatrix() {
double[][] D = new double[m][n];
for (int i=0; i<Math.min(m,n); i++) D[i][i]=A[i][i];
return new Matrix(D);
}
/** Copy the internal two-dimensional array.
@return Two-dimensional array copy of matrix elements.
*/
@@ -239,9 +251,10 @@ public class Matrix implements Cloneable, java.io.Serializable {
public double[][] getArrayCopy () {
double[][] C = new double[m][n];
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = A[i][j];
}
System.arraycopy(A[i], 0, C[i], 0, n);
// for (int j = 0; j < n; j++) {
// C[i][j] = A[i][j];
// }
}
return C;
}
@@ -271,6 +284,10 @@ public class Matrix implements Cloneable, java.io.Serializable {
return vals;
}
public double[] getRowShallow(int i) {
return A[i];
}
/** Make a one-dimensional row packed copy of the internal array.
@return Matrix elements packed in a one-dimensional array by rows.
*/
@@ -1177,4 +1194,30 @@ public class Matrix implements Cloneable, java.io.Serializable {
}
}
/**
* Subtract a line from the indicated line of this matrix in place.
*
* @param rowIndex
* @param B
*/
public void rowSubtract(int rowIndex, double[] v) {
if ((v.length != n) || (rowIndex<0) || (rowIndex>=m)) throw new IllegalArgumentException("Invalid matrix dimensions for rowMinus!");
rowSubtract(rowIndex, rowIndex, v);
}
/**
* Subtract a line from each line of this matrix in place.
*
* @param rowIndex
* @param B
*/
public void rowSubtract(double[] v) {
if ((v.length != n)) throw new IllegalArgumentException("Invalid matrix dimensions for rowMinus!");
rowSubtract(0, m-1, v);
}
private void rowSubtract(int start, int end, double[] v) {
for (int i=start; i<=end; i++) Mathematics.vvSub(A[i], v, A[i]);
}
}

109
src/wsi/ra/math/RNG.java
View File

@@ -1,8 +1,10 @@
package wsi.ra.math;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Random;
import eva2.tools.EVAHELP;
import eva2.tools.Mathematics;
public class RNG extends Random {
@@ -165,8 +167,9 @@ public class RNG extends Random {
public static double randomDouble(double lo,double hi) {
return (hi-lo)*random.nextDouble()+lo;
}
/**
*
* Create a uniform random vector within the given bounds.
*/
public static double[] randomDoubleArray(double[] lo,double[] hi) {
double[] xin = new double[lo.length];
@@ -174,14 +177,35 @@ public class RNG extends Random {
xin[i] = (hi[i]-lo[i])*random.nextDouble()+lo[i];
return xin;
}
/**
*
* Create a uniform random vector within the given bounds.
*/
public static double[] randomDoubleArray(double lo,double hi,int size) {
double[] xin = new double[size];
for (int i=0;i<size;i++)
xin[i] = (hi-lo)*random.nextDouble()+lo;
return xin;
public static double[] randomDoubleArray(double[][] range) {
double[] xin = new double[range.length];
for (int i=0;i<xin.length;i++)
xin[i] = (range[i][1]-range[i][0])*random.nextDouble()+range[i][0];
return xin;
}
/**
* Create a uniform random double vector within the given bounds (inclusive) in every dimension.
*
* @param lower
* @param upper
* @param size
* @return
*/
public static double[] randomDoubleArray(double lower, double upper, int size) {
double[] result = new double[size];
for (int i = 0; i < result.length; i++) {
result[i] = RNG.randomDouble(lower, upper);
}
return result;
// double[] xin = new double[size];
// for (int i=0;i<size;i++)
// xin[i] = (hi-lo)*random.nextDouble()+lo;
// return xin;
}
/**
@@ -193,6 +217,23 @@ public class RNG extends Random {
xin[i] = (hi[i]-lo[i])*random.nextDouble()+lo[i];
return xin;
}
/**
* Create a uniform random integer vector within the given bounds (inclusive) in every dimension.
*
* @param n
* @param lower
* @param upper
* @return
*/
public static int[] randomIntArray(int lower, int upper, int size) {
int[] result = new int[size];
for (int i = 0; i < result.length; i++) {
result[i] = RNG.randomInt(lower, upper);
}
return result;
}
/**
*
*/
@@ -305,17 +346,38 @@ public class RNG extends Random {
* Create a normalized random vector with gaussian random double entries.
*
* @param n
* @param dev
* @return
*/
public static double[] gaussianVector(int n, double dev) {
public static double[] gaussianVector(int n, double dev, boolean normalize) {
double[] result = new double[n];
gaussianVector(dev, result, normalize);
return result;
}
/**
* Create a normalized random vector with gaussian random double entries.
*
* @param n
* @return
*/
public static double[] gaussianVector(double dev, double[] result, boolean normalize) {
for (int i = 0; i < result.length; i++) {
result[i] = RNG.gaussianDouble(dev);
}
Mathematics.normVect(result, result);
if (normalize) Mathematics.normVect(result, result);
return result;
}
public static void main(String[] args) {
double[] v = new double[2];
for (int i=0; i<1000; i++) {
gaussianVector(1., v, false);
EVAHELP.logString(Arrays.toString(v)+"\n", "randtest.dat");
// System.out.println(Arrays.toString(v));
}
}
/**
* Create a uniform random double vector within the given bounds (inclusive) in every dimension.
*
@@ -324,28 +386,13 @@ public class RNG extends Random {
* @param upper
* @return
*/
public static double[] randomVector(int n, double lower, double upper) {
double[] result = new double[n];
for (int i = 0; i < result.length; i++) {
result[i] = RNG.randomDouble(lower, upper);
}
return result;
}
// public static double[] randomVector(int n, double lower, double upper) {
// double[] result = new double[n];
// for (int i = 0; i < result.length; i++) {
// result[i] = RNG.randomDouble(lower, upper);
// }
// return result;
// }
/**
* Create a uniform random integer vector within the given bounds (inclusive) in every dimension.
*
* @param n
* @param lower
* @param upper
* @return
*/
public static int[] randomVector(int n, int lower, int upper) {
int[] result = new int[n];
for (int i = 0; i < result.length; i++) {
result[i] = RNG.randomInt(lower, upper);
}
return result;
}
}